computes the Fourier transform of an approximating Gaussian cumulative distribution function (CDF) for the class of quadratic forms of Gaussian vectors.
Simulates a default distribution for a portfolio of homogeneous obligors where the default driver is normally distributed. Returns mean, variance and the quantile chosen.
Simulates a default distribution for a portfolio of obligors where the (joint) default driver is normally distributed. The dependence structure imposed corresponds to two homogeneous subportfolios driven by two default factors. Returns mean, variance and the quantile chosen.
Simulates a default distribution for a portfolio of homogeneous obligors where individual default drivers are normally distributed. The joint distribution is generated by the use of a t-copula. Returns mean, variance and the quantile chosen.
Simulates a default distribution for a portfolio of obligors where the individual default driver is normally distributed. The dependence structure imposed corresponds to two homogeneous subportfolios driven by two default factors linked by a t-copula. Returns mean, variance and quantile chosen.
uses a generalized eigenvalue decomposition to do a suitable coordinate change. The new risk factors are independently standard normal distributed and the new Hessian matrix (Gamma) is diagonal.
computes the a-quantile for the class of quadratic forms of Gaussian vectors; uses Fourier inversion to approximate the cumulative distribution function (CDF).
computes the unconstrained least squares estimates of the model parameters (B), residuals (u), variance-covariance matrix of the residuals (s), and autocovariance matrix of the time series (g) of a K-dimensional VAR(p) model with/ without intercept
volsurf computes the implied volatility surface using a Kernel smoothing procedure. Either a Nadaraya-Watson estimator or a local polynomial regression is employed. Both are computed with a quartic Kernel. The metric is either moneyness, i.e. strike devided by the (implied) forward price of the und
computes the implied volatility surface using a local polynomial estimation with an automatic bandwidth selection algorithm. The metric is either moneyness, i.e. strike devided by the (implied) forward price of the underlying, or the original strikes.
auxiliary quantlet for cartsplit, creates a vector of volumes: for each node of the tree "tr", calculates the volume of the rectangle corresponding to the node.